Papers with predicting reading

2 papers
On the Role of Context in Reading Time Prediction (2024.emnlp-main)

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Challenge: a new perspective on how readers integrate context during reading time prediction is presented . a recent study shows that the proportion of variance in reading times explained by context is smaller when context is represented by the orthogonalized predictor.
Approach: They propose a technique where they project surprisal onto the orthogonal complement of frequency.
Outcome: The proposed method shows that the proportion of variance in reading times explained by context is smaller when context is represented by the orthogonalized predictor.
Generalized Measures of Anticipation and Responsivity in Online Language Processing (2024.findings-emnlp)

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Challenge: a generalization of classical information-theoretic measures of predictive uncertainty is proposed for online language processing . entropy and surprisal are two commonly deployed information- theoretic measure of predictive uncertainties in sentence processing based on the probability distribution of upcoming sequences of linguistic units .
Approach: They propose a generalization of classical information-theoretic measures of predictive uncertainty in online language processing based on simulations of incremental linguistic contexts.
Outcome: The proposed generalization of classical measures of predictive uncertainty in online language processing yields a positive effect on reading times and cloze completion probability.

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